Establishing Trust through Traceability

I think that nowadays, any time any of us are feeling especially masochistic, we know we can successfully meet our daily exasperation quotas just by turning on the news. Full disclosure, this is in no way meant to be a diatribe on the media and their communication of information related to world events and the US based political circus that continues to unfold before our weary eyes. Rather it’s an observation of what seems to be an emerging theme that continues to grow within our collective consciousness. A pervasive and persistent lack of trust in the validity and transparency of our information sources.

As a scientist, I have been inured to have a healthy degree of skepticism. The education we receive in the sciences in applying research and analytic methods to assess cause and effect drills the concept of “no theory can ever be proven in absolute terms” into us at early and iterative stages of our training. Similarly, as a designer we are conditioned to perpetually seek a “goodness of fit” for any temporary solution that may provide a moderating fix to a constantly evolving problem. At first glance these two disciplines may not seem eminently relatable. As someone who practices both though I can attest that indeed they are. In fact, one of the key elements that unites these two fields is the confidence one has in the veracity and completeness of the data that is guiding their decision making and read of circumstances surrounding a certain problem or opportunity. In scientific analysis, this reliance on normative data to produce predictable results is expressed in quantitative terms referred to as a “confidence interval.” It essentially measures, to the degree, specifically how much the researcher trusts that the information they are using is producing reliable outcomes in which valid inferences can be made. However, in applying a scientific approach to designing solutions to problems in their actual settings I would recommend a slightly different approach to augment trust of information. One that doesn’t require pontificating about “p values” and is far more straightforward. Traceability.

Traceability tools in Systems Engineering provide a complete macro and micro operational assessment that lends itself to the development of subsystem, component, and system support infrastructure matrices allowing for traceability from high-level to low-level design requirements and vice versa. (Blanchard & Fabrycky, 2011). More simply put, these tools allow all stakeholders of an improvement or design team a simple graphic interface to better interpret the connections and relationships between goals and objectives and the variables that are influencing them. Additionally, it provides the system engineer or change management specialist a viable set of quantifiable terms to incorporate into system design parameters and lifecycle performance analysis. Most importantly, it provides a framework for providing comprehensive and easy to digest information related to problem resolution or opportunity improvement. The presentation of an inclusive picture of system factors and their behaviors that everyone can understand and discuss builds trust in stakeholders. This is largely due to the fact that everyone involved in the effort has access to the same complete and easy to comprehend data. Everyone trusts the information informing the design of a system to achieve a specific vision, because in essence everyone is reading off the same sheet of music metaphorically speaking.

One of my favorite traceability tools is what I refer to as a “What/Why” matrix. This is a simple to use and extremely portable tool that can be used essentially by any group of individuals, regardless of background or training, that wish to collectively realize a specific objective. In using this tool, a team leads with the “WHYs” they think a specific goal needs to be accomplished and then ranks these in terms importance on a scale of 1–10 (1 being least important, 10 being most important).

We start with the “WHY’s” in this approach because it automatically introduces “purpose” as opposed to merely “process” into achieving a goal. Evidence supports that most individuals are more likely to commit to accomplishing goals they feel are personally meaningful to them and have the potential to directly improve their own circumstances (Latham & Locke, 2007). Leading with your “WHYs” can also be a critical asset in building team tenacity to get through “the ugly middle” of many projects.

Next the team lists the “WHATs” in the system development process they think will help them accomplish their objective and then ranks these factors in terms of importance.

Finally, the group links which “WHAT” factors they feel will be most instrumental to achieving specific “WHY” factors.

Then the process is simply to multiply the WHAT and WHY weights along with their correlation links to get a system’s design criteria or process step prioritized.

This traceability tool demonstrates how what can at project inception, first perceived as an inconsequential “WHAT” in a project process step can quickly rise to the top in importance because of its potential to support the purpose and meaning behind goal achievement. This method which ties objective achievement to the values that group members find personally valuable is a great way of imbuing team trust. Stakeholders trust that in pursuing a defined goal they are also fulfilling their own hopes and dreams because they can actually see how the process based “WHATs” and the purpose-based “WHYs” are linked and consequentially prioritized. The framework also provides the system engineer or change management specialist some critical metrics to use to inform system design development and performance benchmarking. This approach can be a great first step in integrating co-design into performance driven system development and demystifying data collection and interpretation in design and improvement teams.

In future posts we will discuss how traceability tools and co-design can improve the efficacy of emergent system processes and resilience in system infrastructure. Both critical factors in achieving solutions to “Wicked Problems.”

REFERENCES
1. Blanchard, B., & Fabrycky, W. J. (2011). Systems engineering and analysis (5th ed., Prentice Hall international series in industrial and systems engineering). Boston: Prentice Hall.

2. Latham, G. P., & Locke, E. A. (2007). New developments in and directions for goal-setting research. European Psychologist, 12(4), pp.290–300.

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